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The federal government recently launched an AI literacy program delivered entirely by text message. Jake has completed the first five days, and also looked into a network of teachers, HR professionals, and writers and to ask what they thought. The results were predictable in one direction and surprising in another. This episode is less about the program and more about what it exposes: who gets to define AI literacy, what it's for, and what the cost of doing nothing actually looks like.

What You'll Hear

• Why Jake's reaction to a federally branded program shifted once he actually went through it — and what changed his mind
• The DOL's AI Literacy Framework broken down: five foundations, seven principles, and why the pedagogical thinking behind it is more serious than the branding suggests
• Nathan's argument that 28% of students being able to describe how an LLM works is a real problem — and why understanding the engine matters even if you never plan to drive
• The "professional chef critiquing a how-to-boil-an-egg pamphlet" problem, and who the pamphlet is actually for
• Jake's prediction that the 2026-27 school year is when schools start approaching AI literacy systemically — and what that should and shouldn't mean
• Why excluding AI from your classroom is becoming harder to defend as a pedagogical choice rather than a protective one
• The adult literacy statistic that reframes what's actually at stake when we talk about the AI access gap

Resources Mentioned

• Make America AI Ready — Federal SMS-based AI literacy program from the U.S. Department of Labor. Text READY to 20202 to enroll. [beta.dol.gov/ai-ready]
• U.S. Department of Labor AI Literacy Framework — Five foundational content areas and seven implementation principles for workforce AI readiness. [https://www.dol.gov/agencies/eta/advisories/ten-07-25]
• Slow AI (Sam Ellingsworth) — Substack publication examining AI adoption at a more measured pace. Recommended reading for the "email problem" analogy. [https://theslowai.substack.com/?utm_campaign=profile_chips]
• Quick, Draw! — Google experiment using a neural network to guess your drawings. Referenced as a Day 1 challenge in the Make America AI Ready program. [quickdraw.withgoogle.com/]
• What Uses More? — Tool for comparing energy and carbon footprint of AI tasks vs. everyday activities. [what-uses-more.com]
• Stanford HAI — Stanford's Human-Centered AI institute. Referenced for statistics on AI usage by age and the research on AI in classroom settings. [hai.stanford.edu]
• NCES Adult Literacy Data — National Center for Education Statistics. Nathan cites current figures: 28% low literacy, 29% basic proficiency, 43% proficient — among adults ages 16-65. [nces.ed.gov]

Connect & Continue

Jake writes about AI in education weekly on Substack. Subscribe at whatteachershavetosay.substack.com

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